A State-Space Perspective on Modelling and Inference for Online Skill Rating

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• Dr Sam Power, University of Bristol
• Thursday 07 November 2024, 14:00-15:00
• LR11, Baker Building, CUED.

If you have a question about this talk, please contact Prof. Ramji Venkataramanan.

In the quantitative analysis of competitive sports, a fundamental task is to estimate the skills of the different agents (‘players’) involved in a given competition based on the outcome of pairwise comparisons (‘matches’) between said players, often in an online setting. In this talk, I will discuss recent work in which we advocate for adoption of the state-space modelling paradigm in solving this problem. This perspective facilitates the decoupling of modeling from inference, enabling a more focused approach to development and critique of model assumptions, while also fostering the development of general-purpose inference tools.

I will first describe some illustrative model classes which arise in this framework, before turning to a careful discussion of inference and computation strategies for these models. A key challenge throughout is to develop methodology which scales gracefully to problems with a large number of players and a high frequency of matches. I then conclude by describing some real-data applications of our approach, demonstrating how this framework facilitates a practical workflow across different sports.

This is joint work with Samuel Duffield (Normal Computing) and Lorenzo Rimella (Università degli Studi di Torino), published at JRSS-C.

This talk is part of the Signal Processing and Communications Lab Seminars series.

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